This volume assembles cutting-edge scholarship on scientific understanding, scientific representation, and their delicate interplay. Featuring several articles in an engaging ‘critical conversation’ format, the volume integrates discussions about understanding and representation with perennial issues in the philosophy of science, including the nature of scientific knowledge, idealizations, scientific realism, scientific inference, and scientific progress.

In the philosophy of science, questions of scientific understanding and scientific representation have only recently been put in dialogue with each other. The chapters advance these discussions from a variety of fresh perspectives. They range from case studies in physics, chemistry, and neuroscience to the representational challenges of machine learning models; from special forms of representation such as maps and topological models to the relation between understanding and explanation; and from the role of idealized representations to the role of representation and understanding in scientific progress.

Scientific Understanding and Representation will appeal to scholars and advanced students working in philosophy of science, philosophy of physics, philosophy of mathematics, and epistemology.

chapter 1|13 pages


part I|117 pages

Understanding, Knowledge, and Explanation

chapter 6|16 pages

Factivism in Historical Perspective

Understanding the Gravitational Deflection of Light

chapter 8|19 pages

Topological Explanations

An Opinionated Appraisal

chapter 9|17 pages

Explanatory Power

Factive vs. Pragmatic Dimension

part II|82 pages

Understanding and Scientific Realism

chapter 11|16 pages

Truth and Reality

How to Be a Scientific Realist Without Believing Scientific Theories Should Be True

chapter 12|5 pages

Defensible Scientific Realism

A Reply to Potochnik

chapter 13|6 pages

Different Ways to Be a Realist

A Reply to Pincock

part III|136 pages

Understanding, Representation, and Inference

chapter 17|17 pages

Scientific Representation and Understanding

A Communal and Dynamical View

chapter 22|5 pages

DEKI and the Mislocation of Justification

A Reply to Millson and Risjord

chapter 23|5 pages

DEKI and the Justification of Surrogative Inference

A Reply to Nguyen and Frigg

chapter 26|5 pages

Link Uncertainty, Implementation, and ML Opacity

A Reply to Tamir and Shech

chapter 27|5 pages

Expecting Too Much from Our Machine Learning Models

A Reply to Sullivan

part IV|47 pages

Understanding and Scientific Progress

chapter 28|17 pages

Understanding the Progress of Science

chapter 30|5 pages

The Significance of Justification for Progress

A Reply to Dellsén

chapter 31|6 pages

Scientific Progress without Problems

A Reply to McCoy